Search: “reasoning”

Multilingual Idioms in Sentences and Conversations Across High-, Medium-, and Low-Resource Languages

arXiv:2606.02147v1 Announce Type: cross Abstract: Idiomatic expressions pose a major challenge for multilingual NLP because their meanings shift between figurative and literal usage, often requiring c

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Local Ai

Multimodal Function Vectors for Visual Relations

DGX agent

arXiv:2510.02528v2 Announce Type: replace Abstract: Large Multimodal Models (LMMs) demonstrate impressive in-context learning abilities from few multimodal demonstrations, yet the internal mechanisms

local-aiarxiv-cs-ai

2 Jun 2026

Multimodal Music Recommendation System using LLMs

arXiv:2606.00125v1 Announce Type: cross Abstract: Music recommendation systems typically treat songs as opaque tokens, relying on collaborative interaction histories which overlooks semantic or acoust

Agents

Needles at Scale: LLM-Assisted Target Selection for Windows Vulnerability Research

arXiv:2606.01364v1 Announce Type: cross Abstract: The attack surface of a modern operating system is a haystack: thousands of signed binaries and millions of functions, almost none relevant to any giv

agentsarxiv-cs-ai

Not All Errors Are Equal: A Systematic Study of Error Propagation in Large Language Model Inference

arXiv:2606.02430v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into high-performance computing (HPC) workflows, accelerating scientific discovery through di

Local Ai

NVIDIA Partners With Microsoft on Unified Stack for Agentic AI Deployment, From Windows Devices to Cloud to Local

The agentic AI moment has arrived, but delivering on its promise requires more than good models. It also takes fast hardware, secure runtimes, a responsive data layer and models tuned for long-running

local-ainvidia-blog

OmniOPD: Logit-Free On-Policy Distillation via Speculative Verification

model-releasesarxiv-cs-cl

arXiv:2606.01476v1 Announce Type: cross Abstract: On-Policy Distillation (OPD) trains a student model on its own generative trajectories under dense token-level feedback from a stronger teacher, mitig

OPD+: Rethinking the Advantage Design for On-Policy Distillation

arXiv:2606.01039v1 Announce Type: cross Abstract: On-policy distillation (OPD) is a widely used technique to transfer capabilities from capable teacher language models to the base student models, and

PaintBench: Deterministic Evaluation of Precise Visual Editing

arXiv:2606.00188v1 Announce Type: cross Abstract: While current multimodal models are proficient at open-ended visual editing, executing precise single-answer edits remains an important obstacle. To p

Parameter Alignment Mitigates Catastrophic Forgetting in Multilingual Expert Language Models

model-releasesarxiv-cs-cl

arXiv:2606.00284v1 Announce Type: new Abstract: While continual pretraining~(CPT) is a practical way to extend large language models to new languages, naive finetuning on targeted data erodes existing

PaSBench-Video: A Streaming Video Benchmark for Proactive Safety Warning

arXiv:2606.02443v1 Announce Type: cross Abstract: Between the first visible sign of danger and the moment an accident occurs, there is often a window where intervention remains possible. Video-capable

Permissive Safety Through Trusted Inference: Verifiable Belief-Space Neural Safety Filters for Assured Interactive Robotics

arXiv:2606.02562v1 Announce Type: cross Abstract: Autonomous robots that interact with people must make safe and efficient decisions under human-induced uncertainty, such as their preferences, goals,

PhyScene3D: Physically Consistent Interactive 3D Tabletop Scene Generation

arXiv:2606.01649v1 Announce Type: new Abstract: Generating physically consistent 3D tabletop scenes is a fundamental yet underexplored problem for interactive and generalist robotic learning. The chal

safetyarxiv-cs-cv

PolySpeech-100: A Large-Scale Benchmark for Speech Understanding Across 100+ Languages and Dialects

arXiv:2606.01016v1 Announce Type: cross Abstract: While End-to-End (E2E) Speech-Large Language Models (Speech-LLMs) are rapidly evolving, their evaluation methodologies remain limited to the era of si

Proactive-reactive detection and mitigation of intermittent faults in robot swarms

arXiv:2509.19246v2 Announce Type: replace Abstract: Intermittent faults are transient errors that sporadically appear and disappear. Although intermittent faults pose substantial challenges to reliabi

researcharxiv-cs-ro

Local Ai

ProactiveLLM: Learning Active Interaction for Streaming Large Language Models

arXiv:2606.00523v1 Announce Type: new Abstract: Standard Large Language Models (LLMs) follow a read-then-generate paradigm, causing unnecessary latency and computation. Streaming LLMs alleviate this i

local-aiarxiv-cs-cl

Local Ai

PropLLM: Propagation-Aware Scene Reconstruction for Network Fault Diagnosis

arXiv:2606.00582v1 Announce Type: new Abstract: Network faults propagate layer by layer along topology and protocol dependencies, yet operations systems typically observe only symptomatic alerts at th

local-aiarxiv-cs-ai

PSG-Nav: Probabilistic Scene Graph Navigation via Multiverse Decision Making

arXiv:2606.01313v1 Announce Type: cross Abstract: Open-vocabulary navigation requires embodied agents to manage significant perception uncertainty stemming from semantic ambiguity and model errors. Ho

RAFT: Data Refinement and Adaptive Distillation for Domain Fine-Tuning with Alleviated Forgetting

arXiv:2606.00147v1 Announce Type: cross Abstract: Domain-specific supervised fine-tuning (SFT) often improves in-domain performance at the cost of degrading a model's general capabilities. We view thi

Random Erasing vs. Model Inversion: A Promising Defense or a False Hope?

arXiv:2409.01062v4 Announce Type: replace-cross Abstract: Model Inversion (MI) attacks pose a significant privacy threat by reconstructing private training data from machine learning models. While exi

researcharxiv-cs-cv

RedDebate: Safer Responses Through Multi-Agent Red Teaming Debates

arXiv:2506.11083v3 Announce Type: replace Abstract: We introduce RedDebate, a novel multi-agent debate framework that provides the foundation for Large Language Models (LLMs) to identify and mitigate

safetyarxiv-cs-cl

RefLoRA: Refactored Low-Rank Adaptation for Efficient Fine-Tuning of Large Models

arXiv:2505.18877v4 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) lowers the computational and memory overhead of fine-tuning large models by updating a low-dimensional subspace of the pr

Rethinking Scientific Modeling: Toward Physically Consistent and Simulation-Executable Programmatic Generation

arXiv:2602.07083v2 Announce Type: replace-cross Abstract: Structural modeling is a fundamental component of computational engineering science, in which even minor physical inconsistencies or specifica

Rethinking the Role of Positional Encoding: Sliding-Window Transformers without PE Remain Turing Complete

arXiv:2606.01532v1 Announce Type: new Abstract: Positional encoding (PE) is widely viewed as necessary for transformers to process ordered sequences: without them, the next-token map appears permutati

Retrieve What's Missing: Coverage-Maximizing Retrieval for Consistent Long Video Generation

arXiv:2606.02479v1 Announce Type: new Abstract: Maintaining long-term geometric consistency remains challenging for long-horizon autoregressive video generation. Memory-augmented generative models add

researcharxiv-cs-cv

Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence

arXiv:2606.00570v1 Announce Type: cross Abstract: Parameter-based knowledge editing updates the internal knowledge of large language models (LLMs) via localized weight modifications and has attracted

RoboTrustBench: Benchmarking the Trustworthiness of Video World Models for Robotic Manipulation

model-releasesarxiv-cs-cl

arXiv:2606.01600v1 Announce Type: cross Abstract: Video world models are increasingly used in robotic manipulation, yet existing benchmarks mostly evaluate them under valid, feasible, and safe instruc

Safe2Drive: Evaluating Safe Driving Behaviors of E2E Autonomous Driving Models

arXiv:2606.00191v1 Announce Type: cross Abstract: Recent end-to-end (E2E) autonomous driving policies achieve high driving scores in closed-loop simulations. Yet it remains unclear whether these polic

safetyarxiv-cs-cv

Self-Evolving Hermes Agents: Enterprise AI That Gets Better With Use | Nemotron Labs https://x.com/i/broadcasts/1pJdRRyneOjKW

model-releasesnous-research--x

This likely describes a framework or system for deploying AI agents that autonomously improve their performance over time through continuous learning and adaptation in enterprise environments. The sel

Semantic-Geometric Task Representations for Bimanual Manipulation from Human Demonstrations to Robot Action Planning

arXiv:2601.11460v2 Announce Type: replace-cross Abstract: Learning structured task representations from human demonstrations is essential for bimanual manipulation, where action ordering, object invol

researcharxiv-cs-lg

Agents

Seq-DeepIPC: Sequential Sensing for End-to-End Control in Legged Robot Navigation

arXiv:2510.23057v2 Announce Type: replace-cross Abstract: We present Seq-DeepIPC, a sequential end-to-end perception-to-control model for legged robot navigation in real-world environments. Seq-DeepIP

agentsarxiv-cs-cv

SHERLOCK: Towards Dynamic Knowledge Adaptation in LLM-enhanced E-commerce Risk Management

arXiv:2510.08948v4 Announce Type: replace-cross Abstract: Effective e-commerce risk management requires in-depth case investigations to identify emerging fraud patterns in highly adversarial environme

Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards

arXiv:2510.01167v2 Announce Type: replace-cross Abstract: Aligning large language models to human preferences is inherently multidimensional, yet most pipelines collapse heterogeneous signals into a s

Agents

SkillSmith: Co-Evolving Skills and Tools for Self-Improving Agent Systems

arXiv:2606.01314v1 Announce Type: new Abstract: Recent self-evolving agents have shown that skills can be discovered, refined, and accumulated through execution. However, existing skill-evolution fram

agentsarxiv-cs-ai

Soft-NBCE: Entropy-Weighted Chunk Fusion for Long-Context

arXiv:2606.01101v1 Announce Type: cross Abstract: The quadratic complexity of self-attention remains a bottleneck for Large Language Models (LLMs) processing ultra-long contexts. The Naive Bayes Cogni

SPADER: Step-wise Peer Advantage with Diversity-Aware Exploration Rewards for Multi-Answer Question Answering

arXiv:2606.00593v1 Announce Type: cross Abstract: Large language models are increasingly deployed as tool-augmented agents to acquire information beyond parametric knowledge. While recent work has imp

Tutorials

Spatial Representation Learning Beyond Pixels: Unifying Raster Data and Vector Semantics for Human-Centric Geospatial Foundation Models

arXiv:2606.02374v1 Announce Type: new Abstract: Earth Observation (EO) has fundamentally transformed the monitoring of environmental processes and human activities up to planetary scale. Recent advanc

tutorialsarxiv-cs-ai

Stochastic convergence of parallel asynchronous adaptive first-order methods

arXiv:2606.01787v1 Announce Type: new Abstract: A new class of asynchronous adaptive first-order optimization methods is introduced, comprising asynchronous variants of several popular algorithms. Ver

Strategizing at Speed: A Learned Model Predictive Game for Multi-Agent Drone Racing

model-releasesarxiv-cs-ro

arXiv:2602.06925v2 Announce Type: replace Abstract: Autonomous drone racing pushes the boundaries of high-speed motion planning and multi-agent strategic decision-making. Success in this domain requir

Structured Visual Evidence Decomposition for Evidence-Grounded Multimodal Screening of Obstructive Sleep Apnea-Hypopnea Syndrome

arXiv:2606.00087v1 Announce Type: cross Abstract: Effective pre-polysomnography screening for obstructive sleep apnea-hypopnea syndrome (OSAHS) requires combining clinical risk factors with visible cr

Hardware

SUPREME: A Multi-GPU Framework for Reproducible Image Unlearning Method Evaluation

arXiv:2606.00380v1 Announce Type: cross Abstract: Machine unlearning removes the influence of specific training data from a trained model without retraining it from scratch. Evaluating an unlearning m

hardwarearxiv-cs-ai

T-CLIP: Enabling Thermal Perception for Contrastive Language-Image Pretraining

arXiv:2606.00673v1 Announce Type: new Abstract: Thermal imaging offers a powerful alternative to visible-spectrum vision under challenging conditions such as low illumination and adverse weather, yet

researcharxiv-cs-cv

Tutorials

Tackling the Root of Misinformation by Teaching Laypeople about Logical Fallacies via Socratic Questioning and Critical Argumentation

arXiv:2606.01020v1 Announce Type: new Abstract: Identifying logical fallacies in everyday discourse is challenging for many people. This challenge is amplified in the era of Large Language Models (LLM

tutorialsarxiv-cs-ai

TECCI: Tricky Edits of Collected and Curated Images

arXiv:2606.01213v1 Announce Type: cross Abstract: Despite tremendous recent progress, current text-guided image editing methods still struggle with many aspects of editing involving instruction follow

Industry

the Henry Nowak murder sounds like a completely outrageous parody of the british criminal justice system. it's hard to believe it's real. - …

the Henry Nowak murder sounds like a completely outrageous parody of the british criminal justice system. it's hard to believe it's real. - native Britons can't legally carry a breadknife - for some r

industryelon-musk--x

Tiny Recursive Models for Solving the J2-Perturbed Lambert Problem

arXiv:2606.00895v1 Announce Type: cross Abstract: This paper presents a fast, recursive neural solver for the J2-perturbed Lambert problem based on Tiny Recursive Models (TRM), termed the TRM-Perturbe

ToolFG: Towards Well-Grounded Fine-Grained Image Classification

arXiv:2606.02518v1 Announce Type: new Abstract: Fine-grained image classification (FGIC) has broad applications and has attracted significant research attention. In this paper, we explore a novel para

safetyarxiv-cs-cv

Towards 3D-Aware Video Diffusion Models: Render-Free Human Motion Control with Mesh Tokenization

arXiv:2606.02000v1 Announce Type: cross Abstract: Diffusion models have shown remarkable success in video generation. However, whether such models are truly aware of the 3D structure underlying visual